Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 21, 2024
Date Accepted: Dec 18, 2024
Understanding individual differences in happiness sources using open datasets: Exploring implications for health technology design
ABSTRACT
Background:
The links between happiness and wellbeing has led to great interest in the science of happiness. The design of digital mental health interventions brings many challenges.
Objective:
This paper has two objectives; (i) to present an analysis of how gender may interact with age, marital status and parental status to predict individual differences in sources of happiness, and (ii) to present a preliminary discussion of how open datasets may contribute to the process of designing health related technology innovations.
Methods:
The HappyDB is an open database of 100,535 statements of what people consider to have made them happy within the past 24 hours (49,831 statements) and the last 3 months (50,704 statements). Demographic information is also provided. Binary logistic regression analyses are used to determine whether various groups differed in their likelihood of selecting or not selecting a category as a source of their happiness.
Results:
Gender and age interacted to influence what was selected as sources of happiness, with patterns being less consistent amongst females in comparison with males. For marital status, differences in sources of happiness were predominantly between married individuals and those who are divorced or separated, but these were the same for both genders. Married individuals, single individuals and widowed individuals were all largely similar in their likelihood of selecting each of the categories as a source of their happiness. However, there were some anomalies and gender appeared to be important in these anomalies. Gender and parental status also interacted to influence what was selected as sources of happiness.
Conclusions:
Gender interacts with age, marital status and parental status in the likelihood of reporting affection, bonding, leisure, achievement or enjoying the moment as sources of happiness. Designing digital mental health interventions which are ethical, responsible, evidence based, acceptable, engaging, inclusive and effective for users represents a significant challenge. Content design requires collaboration across several disciplines. Discussions around the content design on digital mental health interventions may benefit from an exploration of new methods for design through data sources. Within this, a discussion of the extent to which our understanding of interactions from non-digital settings may inform requirement gathering for DMHIs is warranted. Clinical Trial: NA
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Copyright
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